Integration of multiple partial point clouds based on estimated parameters in photogrammetry with QR codes

Baba, Keita*; Watanobe, Yutaka*; Nakamura, Keita*; Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of 29th International Symposium on Artificial Life and Robotics (AROB 2024) (Internet), p.751 - 756, 2024/01

Purposeful adaptive sampling of integrated air dose rate maps for visual analysis

Takahashi, Shigeo*; Kurikami, Hiroshi; Sanada, Yukihisa; Sakurai, Daisuke*

ERAN FY2022 Annual Report (Internet), 1 Pages, 2023/04

This study aims to establish a highly accurate evaluation technique for decontamination effects through multilateral and quantitative evaluation of decontamination effects. The applicability of the visual analysis technique was confirmed through a trial analysis.

Fundamental study on 3D structural reconstruction of working environment from sequential images for decommissioning

Hanari, Toshihide; Kawabata, Kuniaki; Nakamura, Keita*; Naruse, Keitaro*

no journal, , 

We develop a three-dimensional (3D) reconstruction method based on sequential images obtained by the remotely operated machine for decommissioning works of Fukushima Daiichi Nuclear Power Station. In this presentation, we propose an image selection method for determining extraction intervals from sequential images using optical flow. We performed the 3D reconstruction introducing the proposed method. From the 3D reconstruction result, we confirmed that duplicate images during the stopping time of the remotely operated machine were almost eliminated from the sequential images, and the proposed method could contribute to reducing computational cost.

Integration of multiple local point clouds based on estimated parameters in photogrammetry with QR code

Nakamura, Keita*; Baba, Keita*; Watanobe, Yutaka*; Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki

no journal, , 

This study proposes a method for integrating reconstructed models by partial-to-partial registration using photogrammetry reconstructed models and QR codes. It has been considered difficult to integrate photogrammetry reconstructed models because the scale of each reconstructed model is different each time. In this study, we solve this problem by placing QR codes of known size in the environment for reconstruction and scaling each reconstructed model based on the size of the QR code. To verify this method, we compared the accuracy of the integrated model with that of the reconstructed model from all images. The comparison results show that a tolerance of 20 mm is highly accurate. We consider that this approach will be effective in reducing the time required for mapping using robotic and photogrammetric methods.